App Monetization

Analytics, App Monetization, Tech Resources, Tips and Advice

A Look Into Social Point's F2P Rewarded Video Ads Strategy With Sharon Biggar

Video ads have been taking the mobile industry by storm as the new business model and with that, comes an abundance of questions as to how to optimize and what are their effects on users. Depending if you are a monetization manager or a product manager, your KPIs may vary, however the ultimate goal is the same: A successful app that maximizes it’s potential.

In a recent panel at GIAF (Games Industry Analytics Forum), Sharon Biggar, Chief Analytics Officer at Social Point led a captivating talk on their personal journey through a series of tests with their users on the effects of video ads and their various formats. The official title was “Video Advertising Strategy in F2P Mobile Gaming”. The video runs for about 25 mins, so if you have the time, give it a watch. Here are the topics covered:

Social Point sought to answer 3 main questions internally before coming to any conclusions regarding their F2P video advertising strategy and I’ll give a break down for each one.

What design options exist for video ads in F2P games?

Generally speaking, there are 4 main ways to integrate video ads into F2P games. Each one has it’s pluses and minuses and are used in different ways. Sharon broke them down into two main categories:

  • Pull Advertising – Pull referring to giving the user the choice to “pull” the video towards them, thus initiating the video ad.
  • Push Advertising – Push referring to forcing the user to watch the entirety of the video in order to continue.

Method 1 – Pull – Gain Currency

Rewarded Video Ads Pull 1 - Gain Currency

I’m sure we are all familiar with this method as its possibly the most prevalent in mobile games. While there are usually daily limits to prevent abuse, the general idea is a user can request to watch a video in return for a reward in forms of gold coins, gems or some other form of in game currency.

Method 2 – Pull – Double Rewards

Rewarded Video Ads Pull 2 - Double Rewards

These rewarded videos tend to appear in two forms as well. One being before initiating a level, the player can watch a video to double the effect bonuses received (gold, gems, experience) upon completing a level. Alternatively, the player is given the option once they’ve completed the level to double their rewards. Generally speaking there are no daily limits on these as they are based upon a user’s direct engagement with the app. Why limit your user’s engagement right?

Method 3 – Pull – Speed Up

Rewarded Video Ads Pull 3 - Speed Up

I’ve encountered (and used) these countless times. Sometimes they come in forms of using in game currency, but specifically here we are talking about watching a video ad in order to speed up an upgrade or improvement. Why wait 5 hours for an upgrade when you can watch a 30 second video to complete the upgrade immediately. Overall it’s a win – win and keeps user’s active.

Method 4 – Push – Forced Video

Rewarded Video Ads Push 4 - Forced Video

An intrusive and often causes some heat from users, due to it’s method, these video interstitials take over the full screen, and force the user to watch / interact with the ad. Some show a countdown before the X appears, others will appear after a few seconds. No reward / incentive is given to the user aside from waiting it out to allow them to continue to play.

Most Requested Video Ad Type

Looking specifically at their game “Dragon City”, in October, they took note of “pull” types of video ads and found some interesting things. *Note: “Dragon Cinema” refers to the gain currency type of rewarded video.

Video Ad Types and Engagement

  • Double Rewards was the most requested type of video ad
  • Interestingly enough that the “Speed Up” type of video ad was less used considering the time spent waiting vs. time spent watching the ad

Do Video Ads Increase Churn?

I think this is one of the most discussed topics right now in the industry. Before I dive into Social Point’s specific study, make sure you check out SOOMLA’s recent report on Lotum and their study on the effect on advertising direct competitors as well. It goes a bit more in depth into the effects on eCPM, churn and has surprising results. We’ve also published a series of blog posts on rewarded video ads which you can find here.

Touching upon Social Point’s study, they found that pulled video ads on similar cohorts (users that played 7 days and that had 14 sessions) had some interesting results. The users that did in fact engage with video ads within the first 7 days, churned significantly less than those who did not watch any video ads. Clearly indicating that for Social Point, video ads were NOT causing an increase in user churn.

Social Point's Results on Do Video Ads Increase Churn

 

FREE REPORT – VIDEO ADS RETENTION IMPACT

 

What About Push Video Ads?

Social Point ran an A/B test where they allowed a control group to see 0 video ads and the second group that saw skippable video ads. There was a clear decrease in retention once forced (push) video ads were displayed. More interestingly, as pointed out by Sharon, is the minor difference between 1 and 3 skippable video ads displayed effect on retention.

Do Push Video Ads Increase Churn?


Do Video Ads Cannibalise IAP Revenue?

Social Point ran an A/B test intending to test the theory that video ads cannibalize the in-app purchase revenue. The results were rather surprising as they did in fact find that the video ads resulted in an 8% decrease in IAP revenue in the control group, however when looking at the overall revenue, the ad revenue resulted in an overall 5% increase in total revenue despite the drop in in-app purchases.

Do Video Ads Canniblize In-App Revenue?

 

CASE STUDY ON ADVERTISERS CHURN & eCPM

 

Oooops!

The tests ran were under the condition that users could watch up to 4 video ads a day, as was the limit set at Social Point. However due to an intentional development change, users were able to watch up to 8 per day. Therefore the results changed a bit.

They quickly found that 39% of their payers (users who were doing IAPs), were watching up to 8 videos resulting in a significant drop in IAP revenue, and even further, the ad revenue was not off setting the drop in IAP revenue and cannibalising the revenue.

Too many rewarded videos results in drop in revenue


Conclusion

  • ”PULL” video ads have no impact on churn
  • ”PUSH” video ads have a small negative impact on churn
  • Video ads DO canniablise IAP revenue
  • IAP + AD revenue can be greater than IAP alone
  • Be careful – don’t allow Payers to watch too many ads

There were two great questions raised by the audience members which really touch upon the importance of analyzing advertisers, churn, eCPM as key drivers.

  • Q1: In the place where you raised the cap on video ads, did you see a drop in the eCPM and was that what impacted the video games short fall in the IAP?
  • A: Yes exactly. As soon as you go to a higher number of video ads, the players are less likely to convert on those video ads.
  • Q2: It is possible to optimize your ad stack to make up for the drop in eCPM?
  • A: Possibly, one of the challenges we’ve had is quite often the mediation platforms don’t have enough inventory.

To close, SOOMLA provides a series of tools helping monetizers, marketers and even product managers analyze critical KPIs on their app’s performance.

 

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Analytics, App Monetization, Game Design, Tips and Advice

4 Proven Tips for Improving Opt-In Rate - Based on Data

If you have been following the SOOMLA blog, attending mobile game conferences or keeping up with the latest mobile monetization trends in some other ways you should already know the following important fact. Improving Opt-in to rewarded videos usually results in an increase of the same proportion in your total ad revenue. This is why many companies that use rewarded videos have been focusing on the opt-in parameter and have been trying to optimize it.

While getting the basic opt-in ratio is easy, there are a few advanced methods for finding hidden opportunities around opt-in rates.

1 – Look at daily opt-in vs. monthly opt-in

Typically, app companies focus on the monthly opt-in – this is the ratio that is normally available by platforms such as Ironsource mediation and what most will allow you to analyze if you send them the impression events. The monthly opt-in, however, only tells part of the story and in many cases we have seen that the daily opt-in can be significantly lower. What that means is that there are users who opt-in to the videos some of the days while not watching videos on other days. Fixing this can usually yield 20-25% more in ad revenue and the way to do it is by taking a close look at your incentives. Will the users need the incentive on a daily basis? If not, try to figure out an incentive that the users will need more regularly.

Definitions
Monthly opt-in – the number of unique users who watched at least one video in a given month out of your total MAU.
Daily opt-in – the number of unique users who watched at least one video in a given day out of your total DAU. The daily opt-in has to be averaged across multiple days to smooth out the fluctuations.

2 – Analyze opt-in for cohorts

Cohort analysis is hardly a new trick for marketers but when it comes to monetization managers it actually is. Comparing the opt-in rate for new users vs. existing users can lead to some pretty interesting insights based on our experience. This might requires some help from your BI team (or simply using SOOMLA’s dashboard) but the hidden opportunity should justify the effort as we have seen up to 2x differences between the two segments. If opt-in is high for new users and declining for long-term users it could be a sign that your incentives are not meaningful enough for your users. In other words users are willing to watch videos but they soon realize that what they are getting in return doesn’t get them very far so they stop. In other situations, the opt-in for new users is low. This could indicate an awareness and training problem. Making your users aware of the option to watch videos early on can fix the problem.

3 – Differentiate users from different traffic sources

One of the interesting patterns we have seen is that users from different traffic sources behave differently when it comes to opt-in ratio. Users who came from paid channels and specifically from video ads often present a higher opt-in ratio compared to organic users. To improve the opt-in ratio for organic users, consider adding some more guidance to highlight the opportunity of watching videos for in-game rewards.

4 – Treat your ad whales to nice Incentives

In recent research we showed that the top 20% of the users contribute 80% of the ad revenue. These so called Ad Whales are the most important segment from an ad revenue perspective. You should focus a lot of your attention to make sure the opt-in rate for this group is as high as it can be. These users typically contribute more than $0.99 and sometimes up to $100. This means that they are as good as payers and you can offer them in-game items that are normally reserved for an actual purchase. However, since you want users of this group to watch a video daily it’s better not to offer them a perpetual item. Some examples of incentives you can give for ad whales:

  • A tank that is normally worth $100 – watch a video to use for a single day
  • Shortening a waiting time that normally costs up to $1
  • 10x coin boost for a short period instead of 2x

Identifying the ad whales is possible by attributing the ad revenue accurately to the user level. The only way to do this accurately today is with SOOMLA Traceback.

We’ve put out a series of posts on the wide topic of Opt-In rates and the importance of them. Feel free to check them out:

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Analytics, App Monetization, Industry Forecasts, Industry News

7 App Monetization Predictions for 2018

As SOOMLA is the 1st company to focus on monetization measurement for mobile apps it only make sense that we will take the lead on predicting some of the trends that will control app monetization in 2018. These predictions are based on our data as well as on observing the market trends in 2017. However, predicting the future is a tricky business so take these with a grain of salt. Here we go – counting 7.

1 – Let the ad whale hunting begin

In 2017 SOOMLA exposed the existence of ad whales – a group of users who contribute over 80% of the app ad revenue and can sometimes make $100 for the app publisher by watching and interacting with ads. In 2018 more and more app companies will invest resources into understanding who the ad whales are, how they behave, what are the best channels to bring more of them and how to adapt the app for this segment. Basically, the same practices app companies applied for the top spenders will be used for the users who generate the big advertising dollars.

2 – Publishers will seek tighter control on ‘rich’ interstitial ad content

2017 introduced a lot of innovation around ad-formats that can be delivered through interstitial containers: Playable ads, interactive videos, dynamic end cards and what not. Publishers who integrated interstitial ads expecting a short ad break in the app flow ended up with an experience they didn’t sign up for. The fact that a longer ad experience with an invisible ‘x’ button has a toll on retention intuitive but SOOMLA also validated that with data and will publish a report about it in Q1/18. In 2017 some publishers started pushing back on these formats and we expect more publishers will want to control these ad experiences in 2018.

3 – More publishers that are also advertisers

In 2016 there were very few ad driven app companies that could afford paid UA campaigns. In 2017 this number grew and in 2018 it will grow even more. Following the footsteps of SOOMLA, more providers are offering tools that give visibility into Ad LTV. In turn, more publishers are aware of where they stand and what CPI levels they can bid. See the post about the steady increase of CPIs and how they are here to stay.

4 – Header bidding will start but adoption will be slower than expected

Header bidding was discussed in many conferences in 2017. The idea is simple and highly beneficial to publishers and some ad providers have launched earlier versions of this model. In 2018, some publishers will test out this model but it will not go into mass adoption just yet. There are too many loose ends at the moment and no sufficient coverage from ad providers. Furthermore, it appears that the some of the leading players are happy to receive bids from others but no so happy to provide the bid out. FB, Google, Mopub, Appodeal and Ironsource are each trying to become the company who will run the auction so they refuse to give a bid out. This means each that each one of them insists on exclusivity which will be a big turnoff for publishers.

5 – Better control over ad experience and creative

Publishers needs ways to control the ad experience as part of the overall app experience. In 2017, SOOMLA and SafeDK started providing solutions in this area. We expect more solutions will become available, more publishers will start using these and ad providers will also start adding more functionality to control ad experience.

6 – More apps will advertise competitors in 2018

Advertising competitors was a big no-no for many app publishers who were concerned their users will churn away and move to the competitor app. In 2018 there are already tools that allows monitoring the eCPM and churn caused by specific advertiser. This means app publishers will be able to apply a data driven approach to this question that was decided with gut instincts until recently. Based on the data we have seen – more publishers will feel comfortable with advertising competitors as a result.

7 – Ads will surpass IAP for mobile game monetization

2017 ended up with a tie between the different monetization models for games. Some studies claimed IAP revenue was still bigger while others showed ad revenue as the winning monetization model. In 2018, there will be no question any more and the clear monetization winner will be ad revenue. Part of the reason for that is the emergence of data tools to measure ad monetization. This makes more publishers feel comfortable with building games that relay heavily on ad revenue.

That’s it – 7 predictions for the new year. Write them down and check if we were right in 12 months.

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App Monetization, Tips and Advice, Video

Top 7 incentives using video ads in your app!

Rewarded videos have been proving to be a highly effective format that balances retention with monetization and typically turn eCPMs of over $20 in the US. However, unlike other ad formats, they require the game designer to build incentives that can be handed to the users when he watches videos. Check out our previous post that talks about mastering the Opt-In ratio to boost rewarded video ad revenue. The general rules of thumb on where to implement rewarded videos are:

  • Designing the incentives from the beginning is easier than adding them after
  • The more evolved the meta game is, the more opportunities for videos there are

Here you can find the most popular incentives to entice users to watch videos:

1. Lives or “save me” option

This is a familiar incentive that allows the player to cheat death. It it widely used in Match-3 games where the meta game typically dictates that a player may only fail 5 times before he runs out of lives at which point he typically has to wait for his lives to replenish. Another version of this incentives appears in action/arcade games where a violent death of the character typically ends the player’s session and an option to keep the session going makes a strong incentive for the user to watch videos.

2. Time related incentives

Warping the game time can be a compelling incentive for the player. In some games, the player is only given a limited time to complete a mission or a screen and is offered to watch a video to gain more time. In other situations, the player wishes to avoid a long wait and is willing to trade that wait for watching a video. A perfect example is upgrading a piece of equipment which takes 2 hours, but if you watch a video ad, it upgrades immediately.

3. In game currency

This one is simple and quite obvious. A bag of gold in exchange for watching a video is one of the oldest offers out there. It’s not the most effective incentive but it’s widely applicable and typically doesn’t require any special hooks to be put in the game for it.

 

FREE REPORT – VIDEO ADS RETENTION IMPACT

 

4. Earnings doubler

The coin doubler is known as a paid item that players can buy. However, a limited time doubler may be offered as an incentive to players who are willing to spend 30 seconds watching a video ad. This type of incentive is popular in idle clicker games and runner games among other genres. There are 2 variations of this incentive:

  • Pre-session – allowing the user to start a session knowing his earnings will be doubled
  • Post-session – popping the question to the user in the session summary screen

5. Re-dealing of a randomly assigned element

In many cases a player get dealt a hand of cards, in other games he opens a pack of collectables and sometimes it’s quests, missions or even songs that the game randomly selects for the player. If a player doesn’t like his options, he can change them in exchange for watching a video.

6. Renting items

Some items in the game can be priced very high and not many users can afford them. Giving them away for a video watch can reduced the perceived value of such items. The compromise is to rent such items for a limited period of time. If an item costs $50 and you expect the users to use it for 30 days renting it for 15 minutes for a video view is maintaining the balance and unlikely to hurt your conversion to payers.

7. The daily spin

Many games offer a daily spin or surprise box as part of their meta game. It’s a great way to make players feel welcomed and keep them in the game. This daily spin often ends with a near miss experience and users are likely to watch a video ad if one is offered in return for an extra spin.

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App Monetization, Research

SOOMLA Webinar # 1 Lotum Case Study on ads and churn

This week we ran our very first webinar at SOOMLA, in an effort to give a bit more visibility and break down to our recent data report on Lotum. The report’s main focus was on the effects of advertising direct competitors on churn and eCPM. Thanks to our very own Yaniv Nizan who took some time to break down the report.

Here is the recording of the webinar! You can find the data report here as well as the full transcript of the webinar below the video.


Start Webinar Transcript

Ben – Hey everyone and welcome to SOOMLA first Webinar, I am Ben Lerner the Director of Marketing and I am joined by our very own CEO, Yaniv Nizan.

Yaniv – Hey, happy to be here, super excited and welcome everyone.

Ben – I’m going to give everyone a very quick intro, these webinars are something we plant o do a monthly basis. There is a lot of great content on our blog including previous reports, but we’re hoping this will help make things a bit more accessible. Today we’re going to be discussing our case study on LOTUM. LOTUM is one of our customers who used Traceback to help gain some really interesting insights. One of which was that specific advertisers resulted in a 3x churn rate, but I think more importantly in all that, it wasn’t quite who they expected.

Before we get into that, Yaniv why don’t explain a bit about SOOMLA and what the Traceback platform is.

Yaniv – Sure, so SOOMLA is an ad measurement platform, and more specifically, we help app publishers measure their monetization. To give you an example, today app publishers don’t know who is advertising in their app, it could a competitor, it could be another app that is taking their users.

Ben – Ahh yes, the infamous black box of advertising that everybody talks about. I’m sure we’ll get more into that, but for now let’s jump straight into the study itself. To give a quick brief on LOTUM, they have a casual word puzzle game called “4 Pics 1 Word” which is available in 8 languages and considered to be one of the top word games in the industry. Yaniv, want to take it from here?

Yaniv – Sounds good, so the context of this report is that we realized that many app developers who used ads, faced the same issue of whether or not to advertise direct competitors.

Ben – Oh yeah absolutely. I personally follow a lot of Indie developer forums being a big gamer myself, and I consistently see issue being raised whenever ad monetization discussion begins.

Yaniv – Yea so the problem is that most app publishers follow their gut feelings when it comes to this. They don’t have any real data to back it up.

Ben – Yea I have seen time and time again – the big warning sign the the skull and crossbones saying – “Don’t allow direct competitors to advertise, they will steal all your users and disappear.”

Yaniv – This sow here Traceback comes in to help Lotus break things down. We can jump into page 3 of the report, and what you can see here is the top 8 advertisers that LOTUM had in the US in the period we measured this. For the purpose of this report we defined Churn as users who clicked on an ad inside the game, but didn’t come back to the game within a 7 day window after clicking on the ad. So if the user did not come back, they are considered to be a churned users. So what you can see here, some of the games like Game of War for example, has 3x more churn. So when Game of War is being advertised in LOTUM app, users that clicked on that are 3x more likely to not come back.

Ben – Really? Okay so seems kind of crazy the nobody has analyzed this until today. Just a question though, what are the actual numbers we are talking about here? Are we talking about churning in the thousands of users, hundreds of users? All I am seeing here are graphical displays.

Yaniv – Yea so this report doesn’t show the exact numbers. Obviously this is confidential information that LOTUM preferred to keep to themselves and we totally respect that for our customers. To give you a range where this could be, typically if we look across all of our customers the churn rate caused by advertisers comes between 3% up to 25% caused by specific advertisers.

Ben – So to fully grasp what you’re talking about, your saying that the potential range is not 3x but closer to 8x. Whats the biggest range you’ve ever seen in a single game?

Yaniv – Yea so 8x is across all the games that we are seeing and I’m saying games, but its also broader than that, as we also have non gaming apps as well. But in a single app or game, we’ve seen a difference of up to 4.5x churn rate between the lowest and highest churning advertiser.

Ben – Wow, but correct me if I’m wrong, isn’t Game of War not a direct competitor to 4 Pics 1 Word?

Yaniv – Yea and this is the part that also surprised us a bit and also Lotum. So Game of War isn’t even a word game and Lotum’s app is. These games are very difference in nature and still this is the advertiser that was taking away the most churn. So when we say this, we wanted to look specifically about whats happening with direct competitors vs non and take the opportunity to dig a little deeper.

Ben – So its literally going completely opposite to whats the industry standard right now.

Yaniv – So as I mentioned before we had a drill down about this specifically. If you look at pages 6 and 7, this is the area where we focused on that. So we looked at all the advertisers and classified them into groups. We didn’t just look at the top eight, but many more. The groups were: Non Games, Other Games and Direct Competitors. For each one of these advertisers we measured two parameters: The churn rate of advertisers in this group and eCPM.

Ben – So thats very interesting and I imagine this means that there is no negative implications for advertising direct competitors. Is it safe to assume that competitors will be paying more to advertise in the app?

Yaniv – Yea so great question, so if you look at page 7, this is what I was saying before. We also measured the eCPM of each one of these groups and what we have seen quite consistently is that direct competitors do pay more to be placed in the app. But as you mentioned before a lot of time there is no negative impact.

Ben – Great so I think these case studies are great but I think a lot of our users would love to see how this has all been possible. Do you think we can spare a few minutes and jump into the Traceback platform itself?

Yaniv – Absolutely, so let’s jump into Traceback. For the sake of this section, we’ll use our demo app called Muffin Rush, which contains a bunch of sample data. So the data is based on one of our live apps, but we masked everything to protect the confidential data of course.

Ben – Yea of course, makes sense. Sow act does it look like once I login, what am I going to start seeing, what data am I going to start seeing? Go for it.

Yaniv – Cool so now that I clicked on the app, I’m int he overview screen once I logged in. This shows you aggregated data and allows you to follow the trends for the app.

Ben – Okay but I see there are some deeper drill down screens. Which one should we be focusing on? I’m thinking the section most most relevant is one that we are looking at advertisers themselves. Can you breakdown what we are looking at?

Yaniv – Yea so on the top menu you can see all the different breakdown screens. One for segmenting and AB testing, another to analyze how ads impact your marketing activity, another how to optimize your waterfall. But as you me toned, the most interesting one for this discussion is the advertiser screen.

Ben – I see you already have the US country filter selected and the interstitial ad types.

Yaniv – Yea so obviously it makes sense to compare advertisers using the same ad format and country, otherwise you’ll be comparing apples to oranges and you don’t want to do that. I can also select different date ranges and change the filters as well.

Ben – Great os it looks pretty intuitive. Each row represents a specific advertiser. Under each one you’re seeing whats the eCPM, whats the total revenue, how many ads were shown etc.

Yaniv – Yea so you can slo control the columns via the three dots on the right to control which columns are being displayed.

Ben – Are there any further drill downs we can go from here?

Yaniv – Yea so if I click on word crossy for example, I get a more specific drill down to them. So this advertiser is coming to my app both through Facebook Ad Network as well as AdMob and actually I can see here that both are paying different eCPMs for this advertiser.

Ben – Well this looks great and I’m sure it has some incredible applications for anybody that knows how to break through all of this data. Tying back to the report itself, LOTUM had asked you guys to produce this report for them, but is this something you do for all of your customers.

Yaniv – Right so we obviously understand that the amount of data can be overwhelming and not everyone has the time to really analyze everything and this is why we assign a dedicated customer success manager who’s job it is to help the customer identify areas where they can improve. This was the case with LOTUM. We gave them this report and allowed them identify different areas to improve.

Ben – Great Yaniv, I wanted to thank you for taking the time to break down the report and more importantly, showing us the the results of Lotus are indeed possible for others given the insights.

Yaniv – Yea was my pleasure and hopefully we’ll run more of these soon with other key features,

Ben – Absolutely. Shout out to everyone for attending. We’ll be posting the recording of the webinar and some of the questions we’ve received throughout. See you all next time for another SOOMLA session. Thanks guys!

End Webinar Transcript

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App Monetization, Research

Header image - the SOOMLA ads and churn case study is out for Q4 2017, full of insights

We are excited to announce our new “Ads and Churn Case Study with Lotum” report today. This is one of the many industry data reports that we will continue to publish providing important insights related to monetization through ad revenue. Our new reports focuses on the effects of advertising director competitors and their effects on eCPM, churn and seeks to identify which advertisers may be stealing your traffic.

You are welcome to download the report through this link or via the banner to the right.

Would also be great if you can help us spread the word by sharing my post on Linkedin.

Linkedin post about mobile monetization report - q2 2017

 

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Analytics, App Monetization, Tips and Advice

3 reasons to track 1st Impression eCPM and not average eCPM

App Publishers who monetize with ads often face the need to compare between ad-networks. Which one offers stronger monetization? Is the network declining in strength? Who should i put first in the waterfall? The common practice today is to look at the average eCPM but actually looking at the 1st impression eCPM is a much better approach. Here are 3 reasons for that.

Networks put their best campaign first

Each ad network has internal optimizations mechanisms in place. Some have algorithmic approach that try to predict the eCPM of each potential ad given who is the user and all the data they have about him. Others have more simplistic priority lists. Either way, when the network sees the user for the 1st time in a given day, it will try to put the best ad for that user. In later impressions, they have to circulate in other ads, their 2nd best, 3rd best and so on.

Average eCPM is a self fullfilling prophesy

Average eCPM on the other hand is influenced by many parameters other then the network’s stregth. In situations where the average eCPM is used to determine the priority between the networks it acts as a self fullfilling prophesy. To understand this, let’s look at the two ends of the priority list:
The Network with First Priority – This network gets more 1st impressions than any other network as long as it has fill for them. This drives the average up. At the same time, the network also wants to stay at the top and knowing that the publisher is looking at the average eCPM it is likely to set a price floor that will eliminate the low eCPM campaigns. This will also drive the average eCPM up.
The Network with the Low Priority – This network is getting less 1st impressions so their average will be lower. Even if the network landed a major campaign it will not get a lot of exposure and will not be able to drive the eCPM up. At the same time, the low priority network can’t shut down the low eCPM campaigns as that will completely choke the delivery for their advertisers and will cause a new bag of issues for the network.

 

FREE REPORT – VIDEO ADS RETENTION IMPACT

 

Changes in 1st impression eCPMs are clear triggers for action

Tracking different parameters is a good practice but tracking becomes much more powerful when it’s connected to actions. When you track the average eCPM and you see a drop in that paremeter for one of the ad-networks there could be a few potential explanations. For example, if that network is getting a high percentage of later impressions it would bring down the average. The 1st impression eCPM is less influenced by how you are using the demand source and is a better indicator of the quality of the demand. A drop in the 1st impression eCPM can be caused by the ad-network losing an important advertiser or by them changing the rev-share on their end. Either way, it’s a good reason to look for new partners to take the lead.

Tracking 1st impression eCPM – Easier than ever

The reason why more company focus on average eCPM rather than 1st impression eCPM is that this is the information the ad-networks are making available on their dashboards. Publishers that use SOOMLA, however, have easy access to reports about the 1st impression eCPM over time and the 1st impression eCPM of every single campaign by each ad-network in addition to the average eCPM.

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Analytics, App Monetization, Tips and Advice

Easy In-App Events That Can Give You Insight on Your App's Performance

No matter what you are looking to achieve, in-app events are a great way to go about getting performance indicators on some of the central issues faced by your app’s growth. While it might sound great to track every swipe, click, open or close event within your app, it can become a bit overwhelming to make use of all the data.

There is already an established list of benchmarks that should be closely monitored to give you some insights about your app’s performance, however the focus here is to dive into specific in-app events and how they should be approached.

Here is the short list (we could have made it much larger):

Registrations and the dreaded drop-off

Registration drop-offs are the bane of every app. We work so hard to get the quality traffic and the installation, but when it comes to registering – poof they are gone. The golden rule is reduce the amount of steps required for the user to complete the registration. With each additional step, the drop off chance is higher.

Solution – Keep a close eye on your registration drop offs. Identify key steps that are causing it and work to reduce. A/B testing is key here.

Tutorials

Some apps have them, some don’t, but it all depends on how much of an onboarding experience you want to provide the new user. Whether or not they are effective or not, I’ll let you be the judge, however if you do have them, a user’s completion of the tutorial can give you some insight as to how engaged your users are.

Solution – Overall on-boarding completion is a good metric to keep an eye on, however if the number is significantly low, it would be worthwhile to set up multiple in-app events for various stages to check out where the drop-offs are occurring.

User Progression

How quickly your user’s progress through your beginning game content is a great identifier on how your app is performing, but also can give you great insights on which users to segment and target specifically. Conversely, those users who move through the content slow should also be identified.

Solution – Logging several events throughout (beginning, middle, end), should be examined to monitor drop-offs and provide some insights on how engaged your users are.

Video Ads Completion

There are a multitude of parameters to look at and analyze when considering how effective your video ads are. Several studies have been put out, but the macro trends show that there has been a big shift towards video ads and its respective portion of ad revenue.

Where you place your ads within your app and how frequently can influence your revenue, uninstall rate, player experience and many other key KPIs.

Solution – Monitor and A/B test the placement and frequency of your video ads. They can have a big effect, but also have the potential to damage your app’s overall performance. Also be sure to check out our post on optimizing your opt-in rate for video ads which can help boost your ad revenue significantly.

FREE REPORT – VIDEO ADS RETENTION IMPACT

In-App Purchases

If your app has in-app purchases, an obvious tell-tale how your app is performing is how many of your users are making purchases. It is a great indicator of how engaging your app is, be it either via content or level of addiciton. A user’s purchasing behaviour can then be leveraged for future purchases. Knowing what your users have purchased and how much they have spent in the past are key for segmenting promotions and sales for specific users.

Solution – If the frequency of in-app purchases are very low, try to lower the costs / increase the offer to entice users. The ultimate goal is finding that sweet spot between making the in-app purchases valuable but not too much so that they make it too easy for the user.

Conclusion

Very likely each app has it’s own category specific in-app event that is closely monitored, however we tried to focus on the basics that touch on many different types of apps. We hope that this list helps you gain some insights on how your app is performing.

If you can think of any other critical in-app events that should be added to this list, let us know!

 
 

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Analytics, App Monetization, Guest Post, Tips and Advice

Call App's Jonathan Raveh - Best Ways to Increase Ad LTV

Jonathan Raveh is a mobile monetization expert and the Director of Monetization at CallApp, a world leader in Caller ID & Call Recorder services.

One of the interesting abnormalities in the world of app monetization is the relatively low number of people assigned to it. UA acquisition departments usually take up much more personnel, while the main focal point for generating revenues in an app development company, is usually understaffed or assigned to the product team.

While this may not be the best policy, this is definitely the reality. Monetization is a shared responsibility across many departments in the company, including UA, Product & Marketing. This leaves any dedicated monetization employees in a serious dilemma – with low resources, where should they invest their time and effort the most? With ad monetization getting bigger even for IAP focused apps, this is a true challenge.

CallApp, a caller ID & call recorder app is one of those apps. With over 35M installs worldwide, our app is totally free to use, and while there are some IAP offers in place, most revenue is ad-related. Joining a very small team and being solely responsible for the app monetization efforts, I faced this challenge from the very first day – FOCUS. Granted, there is no limit to what you can focus on when you’re in charge of monetization. However, there is a definite time limit to (1) hours in the day and (2) Being able to concentrate without making too many mistakes analyzing data. The other major constraints are limited development resources and UX.

These limitations ultimately shaped up our 4 major, strategic responsibilities for mobile ad monetization that rise over and influence the day-to-day actions and task. We’ve put them to that to the test, and came up with some findings that helped figure out exactly what task our time will be best spent on.

Ad Frequency & Location

Right off, this is that one is the very basic element. Forget ad partners, forget business – determining ad frequency has a huge effect on the entire app eco-system. In the short run, ad location, and more importantly ad frequency influence development, usage, data, UX, user satisfaction. In the long run – ratings, reviews, PR, ASO and much more. We found that these types of changes may amount to 50% change in revenue. In term of development time, this is not an easy task, but as these changes aren’t usually done on a daily or weekly basis, it’s definitely barrable.

Focus on GEO’s

Ad monetization wise, app developers tend to give attention to 1 of the following:

  • High eCPM yielding counties
  • High impression yielding countries
  • Countries that possess 1+2

In more cased than not, attention means full attention, and that means that countries that do not generate high impression volume or high eCPM are simply neglected. In most cases, neglected GEO amount to more than 25% of traffic. In order to optimize those loose ends, there is usually a need to work with more localized ad networks, expand and complicate your ad waterfall and sometimes work with additional ad formats. Not only does this burden your development team, it also creates tons of work for the person in charge of monetization. So, a tough decision. However, this clear subjective decision that varies from one app to another, usually influences over 20% of revenues, in average.

Adding More Ad Networks

The actual deciding factor on how many ad networks an app needs, depends heavily on the level of monetization you want to achieve. The actual number of monetization networks an app needs relies on 4 parameters, known as the FORM model which we developed in CallApp: Formats, OS, Regions, Maximization. The entire model has been widely explained (here), yet it embodies another critical decision in the maximization element: how much work are you will to make to get those extra 10 percent of revenue. These 10 remaining percent of revenue require some work from the IT side (adding more ad networks), and a lot of Monetization hard-labor analytics.

 

FREE AD NETWORK COMPARISON SPREADSHEET

 

Setting Floor Price

If you monetize your app using Facebook and Google (and a few others), this is a must. There are automated mechanisms in place, by both ad giants, to make sure you generate a minimal amount of revenue, but true optimization cannot be reached without designated price floors.

When it comes to price floors, there’s a major difference between Google & Facebook: While Google’s price floor (via Admob’s & AdX) tend to merely set a floor from which your eCPM cannot go under, FAN’s floor prices are actually ‘target eCPM’, a level that sets the goal for its performance to reach, regardless of any other elements – CTR, impression and mainly fill rate. However different, both price floor mechanisms are a pretty powerful tool. They require no effort from the development team, yet a lot of attention from the monetization team. Price floors are affected by anything from ad frequency, GEO’s and seasonality, so they need to be monitored on a daily basis. A hell of a lot of work, with a 30% revenue bounce potential.

After experiencing the effects of these 4 pillars of strategic monetization decisions on all sides – revenue, product, development time, monetization time, etc – we were able to visualize these strategies, to better understand the role of the monetization team.

Effects Compared To Development Team Work:

Development Resources for AD LTV

Effect Compared to Monetization Team Work:

Day-To-Day Resources

The last 7 months at CallApp taught me, first and foremost, that in ad monetization, focus & prioritization are strategic decisions. Time equals money, but it’s a lot more than your money – it’s the money you could have been generating doing something else to improve results. Not all apps will follow the same path in this time/effect/results equation, many simply just into the pool of the day-to-day duties without taking a single moment to breath and think about what they want to gain. The CallApp experience has definitely taught me that everyone should give it some serious thought. That will ultimately lead to better result in the long run.

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App Monetization, Tips and Advice

Hiring a ROI Monetization Manage, a full ROI formula and explanation

Many companies ask themselves these days if they should be hiring a Monetization Manager now or wait until it’s volume is larger. In this post we will try to provide a simple framework for thinking about this question.

Ads first games vs. IAP first games

There are two types of companies to consider for this question. Before you continue, you should ask yourself which type of company are you. The framework for evaluating the merits of hiring a monetization manager differs a bit between the two types of companies. Here is the profile for each one:

Ad first games – These are typically smaller companies. If you are an ad supported company and still debating the monetization manager question it’s unlikely that you have more than 15 employees. These companies tend to have a mix of at least 3 ad formats from this list: banners, native, interstitials, video and rewarded video.

IAP first games – These are typically more established companies who already do well with IAP and treat ads as a secondary channel. The ad formats in use here are mostly rewarded videos and sometimes offer walls.

The basic formula

There are 2 conditions to be met before you hire a monetization manager:

  • The ROI condition
  • The focus condition

The ROI condition

[monthly ad revenue] x [improvement opportunity ratio] x [risk factor] > [monetization manager full cost]

Where:

  • Monthly ad revenue – how much your app is making every month from advertising
  • Improvement opportunity ratio – Estimation of how much you can improve
  • Risk factor – the chance of that improvement actually happening
  • Monetization manager full cost – Salary + social benefits + taxes + direct overhead increase + cost of tech tools + cost of projects he will drive

The focus condition

The focus condition is looking at the same formula but instead of justifying the direct cost, you are estimating the opporunity cost. The focus condition is more relevant if you are projecting that the monetization manager will be driving many requirements to R&D and BI departments. We will see how to evaluate how much effort the monetization manager will require in the paragraphs below.
The way to think of opportunity cost is usually top down. Let’s say that the goal of the company is to double in revenue within 12 months. This means that each quarter you are looking to get 20% growth. Most companies can’t contain more than 2 focuses each quarter and some say 1 is enough. This means that if the monetization manager and all the tasks associated with him will not generate 10% increase it’s not meeting the focus condition. The formula will look as follows:

[improvement opportunity ratio] x [risk factor] > [Required quarterly improvement] / [Quarterly initiatives count allowed]

Estimating the improvement ratio

For IAP first games

  • Improving opt-in ratio for rewarded videos – high product and R&D effort – can double or triple ad revenue when combined with A/B testing.
  • Adding more demand partners – medium product and R&D effort – the improvement in ad revenue can be up to 50% depending on current status (see full explanation below)
  • Applying CPM price floors and cutting fixed CPM deals – no R&D effort – up to 15% improvement
  • Blocking low eCPM advertisers and optimizing volume for high eCPM ones – no R&D effort – up to 15% improvement
  • Setting different ad strategies for different segments – low R&D effort – up to 30% improvement
  • Acquiring users who respond better to ads – no R&D effort – up to 50% improvement

For Ads first games

  • Optimizing the frequency and mix of ad-formats – medium R&D effort – can improve ad revenue up to 50%
  • Adding more demand partners – medium R&D effort unless done as S2S – the improvement in ad revenue can be up to 50% depending on current status (see full explanation below)
  • Applying CPM price floors and cutting fixed CPM deals – no R&D effort – up to 25% improvement
  • Blocking low eCPM advertisers and optimizing volume for high eCPM ones – no R&D effort – up to 15% improvement
  • Setting different ad strategies for different segments – mid R&D effort – up to 30% improvement
  • Acquiring users who respond better to ads – no R&D effort – up to 50% improvement

 

FREE REPORT – VIDEO ADS RETENTION IMPACT

 

How much your ad revenue can improve by adding demand partners

The improvement ratio per ad-format is driven by how strong your demand and fill rates are currently. We included a basic formula that we found helpful but you should do a better job assessing this by looking at specific countries and diversified demand. We also recommend Jonathan Raveh’s post on this subject. Here is a simple formula to start with:

(2x[number of ad-networks serving banners]+1)x[banners revenue ratio from total]/2x[number of ad-networks serving banners]-1

Estimating the cost of the monetization manager

$8K/month or $96K per year is a nice salary for a monetization manager in US. The taxes and benefits in US can come to 25% to 40% on top of the salary. Office space and immediate overhead per employee can be around $500 based on WeWork rates. In addition, we should add the average license cost of SOOMLA ($3,000) since having a monetization manager and not giving him the right tools to optimize would be moot. The total comes to $13,500 – $15,000.

Estimating the risk

The risk ratio is slightly harder to estimate. You should think of all the things that can go wrong and try to assign probabilities. Here are some items to consider:

  • Bad hiring can set you back
  • If you can’t afford a SOOMLA license your risk will be higher
    • The monetization manager will not be able to a/b test the ad revenue so optimizations might have a negative impact
    • His ability to set the right price floors will be limited
    • He will not be able to analyze and optimize on a campaign level
    • Segmentation will not be possible for him
    • The users that are being acquired by the UA team will not be a good fit for ads
  • IAP first apps monetize mostly with rewarded video where negotiating eCPM price floors with ad-networks is only possible for high volume apps.

Example – finding the ad revenue threshold for hiring

Let’s look at one example of using the formula. We can estimate that the total opportunity to improve is 60%, the risk factor is 50% and the total cost of the monetization manager will be $15,000.

[monthly ad revenue] x 60% x 50% > $15,000

To satisfy this condition we need an ad revenue of at least $50K / month or $600K annually. The numbers we choose are reasonable so if you have this level of ad revenue and you are not hiring a monetization manager you are probably leaving money on the table. Of course, if you have $1M/month from IAP and only $50K in ad revenue, you might have bigger fish to fry first. This is where the focus condition comes in to play. Make sure you evaluate both before you make the decision.

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SOOMLA - An In-app Purchase Store and Virtual Goods Economy Solution for Mobile Game Developers of Free to Play Games